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Updating high-utility pattern trees with transaction modification

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Abstract

Traditional association-rule mining only concerns the occurrence frequencies of the items in a binary database. In real-world applications, customers may buy several copies of the purchased items. Other factors such as profit, quantity, or price should be concerned to measure the utilities of the purchased items. High-utility itemsets mining was thus proposed to consider the factors of quantity and profit. Two-phase model was the most commonly way to keep the transaction-weighted utilization downward closure property, thus reducing the numerous candidates in utility mining. Most methods for finding high-utility itemsets are used to handle a static database. In practical applications, transactions are changed whether insertion, deletion, or modification. Some itemsets may arise as the new high-utility itemsets or become invalid knowledge in the updated database. In this paper, a maintenance Fast Updated High Utility Pattern tree for transaction MODification (FUP-HUP-tree-MOD) algorithm is thus proposed to effective maintain and update the built HUP tree for mining high-utility itemsets in dynamic databases without candidate generation. Experiments are conducted to show better performance of the proposed algorithm compared to the two-phase algorithm and the HUP tree algorithm in batch mode.

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Acknowledgments

This research was partially supported by the Shenzhen Peacock Project, China, under grant KQC201109020055A, by the Natural Scientific Research Innovation Foundation in Harbin Institute of Technology under grant HIT.NSRIF.2014100, and by the Shenzhen Strategic Emerging Industries Program under grant ZDSY20120613125016389.

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Authors and Affiliations

  1. Innovative Information Industry Research Center (IIIRC), School of Computer Science and Technology, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen, China

    Chun-Wei Lin & Wensheng Gan

  2. Shenzhen Key Laboratory of Internet Information Collaboration, School of Computer Science and Technology, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen, China

    Chun-Wei Lin

  3. Medical School, Shenzhen University, Shenzhen, China

    Binbin Zhang

  4. Department of Electrical Engineering, National Cheng Kung University, Tainan, Taiwan

    Bo-Wei Chen

  5. Department of Multimedia, Sungkyul University, Anyang-si, South Korea

    Seungmin Rho

  6. Department of Computer Science and Information Engineering, National University of Kaohsiung, Kaohsiung, Taiwan, Republic of China

    Tzung-Pei Hong

  7. Department of Computer Science and Engineering, National Sun Yat-sen University, Kaohsiung, Taiwan, Republic of China

    Tzung-Pei Hong

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  1. Chun-Wei Lin
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  2. Binbin Zhang
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  3. Wensheng Gan
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  4. Bo-Wei Chen
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  5. Seungmin Rho
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  6. Tzung-Pei Hong
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Correspondence to Binbin Zhang.

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Lin, CW., Zhang, B., Gan, W. et al. Updating high-utility pattern trees with transaction modification. Multimed Tools Appl 75, 4887–4912 (2016). https://doi.org/10.1007/s11042-014-2178-9

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  • DOI: https://doi.org/10.1007/s11042-014-2178-9

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